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Grid/Grid/algorithms/iterative/AdefMrhs.h
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/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/AdefGeneric.h
Copyright (C) 2015
Author: Peter Boyle <paboyle@ph.ed.ac.uk>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#pragma once
#include <Grid/algorithms/multigrid/MrhsPreconditioner.h>
/*
* Compared to Tang-2009: P=Pleft. P^T = PRight Q=MssInv.
* Script A = SolverMatrix
* Script P = Preconditioner
*
* Implement ADEF-2
*
* Vstart = P^Tx + Qb
* M1 = P^TM + Q
* M2=M3=1
*/
NAMESPACE_BEGIN(Grid);
//////////////////////////////////////////////////////////////////////
// Two-level CG family on a vector of right-hand sides, with the
// preconditioner (M1 and Vstart) as an MrhsPreconditioner object:
// fPcg flexible PCG, one Krylov per rhs, shared M1 call
// PrecBlockCGrQ preconditioned BlockCGrQ (arXiv:2409.03904 s2.2);
// assumes a stationary preconditioner; not the
// production choice (its linalg grows as nrhs^2)
// Also a LinearFunction<Field>: one rhs is the nrhs=1 case.
//////////////////////////////////////////////////////////////////////
enum class MrhsCGAlgorithm { fPcg, PrecBlockCGrQ };
template<class Field>
class TwoLevelCGmrhs : public LinearFunction<Field>
{
public:
using LinearFunction<Field>::operator();
RealD Tolerance;
Integer MaxIterations;
GridBase *grid;
MrhsCGAlgorithm Algorithm;
LinearOperatorBase<Field> &_FineLinop;
MrhsPreconditioner<Field> &_Precon;
MultiRHSBlockCGLinalg<Field> _BlockCGLinalg;
TwoLevelCGmrhs(RealD tol,
Integer maxit,
LinearOperatorBase<Field> &FineLinop,
MrhsPreconditioner<Field> &Precon,
GridBase *fine,
MrhsCGAlgorithm alg = MrhsCGAlgorithm::fPcg) :
Tolerance(tol),
MaxIterations(maxit),
Algorithm(alg),
_FineLinop(FineLinop),
_Precon(Precon)
{
grid = fine;
};
// mrhs entry point
virtual void operator() (std::vector<Field> &src, std::vector<Field> &x)
{
if ( Algorithm == MrhsCGAlgorithm::PrecBlockCGrQ ) SolvePrecBlockCG(src,x);
else SolveSingleSystem(src,x);
}
// LinearFunction entry points
virtual void operator() (const Field &src, Field &x)
{
std::vector<Field> S(1,src);
std::vector<Field> X(1,x);
(*this)(S,X);
x = X[0];
}
virtual void operator() (const std::vector<Field> &src, std::vector<Field> &x)
{
std::vector<Field> S(src);
(*this)(S,x);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
// Thin QR factorisation (google it)
////////////////////////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
//Dimensions
// R_{ferm x Nblock} = Q_{ferm x Nblock} x C_{Nblock x Nblock} -> ferm x Nblock
//
// Rdag R = m_rr = Herm = L L^dag <-- Cholesky decomposition (LLT routine in Eigen)
//
// Q C = R => Q = R C^{-1}
//
// Want Ident = Q^dag Q = C^{-dag} R^dag R C^{-1} = C^{-dag} L L^dag C^{-1} = 1_{Nblock x Nblock}
//
// Set C = L^{dag}, and then Q^dag Q = ident
//
// Checks:
// Cdag C = Rdag R ; passes.
// QdagQ = 1 ; passes
////////////////////////////////////////////////////////////////////////////////////////////////////
void ThinQRfact (Eigen::MatrixXcd &m_zz,
Eigen::MatrixXcd &C,
Eigen::MatrixXcd &Cinv,
std::vector<Field> & Q,
std::vector<Field> & MQ,
const std::vector<Field> & Z,
const std::vector<Field> & MZ)
{
RealD t0=usecond();
_BlockCGLinalg.InnerProductMatrix(m_zz,MZ,Z);
RealD t1=usecond();
m_zz = 0.5*(m_zz+m_zz.adjoint());
Eigen::MatrixXcd L = m_zz.llt().matrixL();
C = L.adjoint();
Cinv = C.inverse();
RealD t3=usecond();
_BlockCGLinalg.MulMatrix( Q,Cinv,Z);
_BlockCGLinalg.MulMatrix(MQ,Cinv,MZ);
RealD t4=usecond();
std::cout << " ThinQRfact IP :"<< t1-t0<<" us"<<std::endl;
std::cout << " ThinQRfact Eigen :"<< t3-t1<<" us"<<std::endl;
std::cout << " ThinQRfact MulMat:"<< t4-t3<<" us"<<std::endl;
}
virtual void SolvePrecBlockCG (std::vector<Field> &src, std::vector<Field> &X)
{
std::cout << GridLogMessage<<"HDCG: mrhs fPrecBlockcg starting"<<std::endl;
src[0].Grid()->Barrier();
int nrhs = src.size();
// std::vector<RealD> f(nrhs);
// std::vector<RealD> rtzp(nrhs);
// std::vector<RealD> rtz(nrhs);
// std::vector<RealD> a(nrhs);
// std::vector<RealD> d(nrhs);
// std::vector<RealD> b(nrhs);
// std::vector<RealD> rptzp(nrhs);
////////////////////////////////////////////
//Initial residual computation & set up
////////////////////////////////////////////
std::vector<RealD> ssq(nrhs);
for(int rhs=0;rhs<nrhs;rhs++){
ssq[rhs]=norm2(src[rhs]); GRID_ASSERT(ssq[rhs]!=0.0);
}
///////////////////////////
// Fields -- eliminate duplicates between fPcg and block cg
///////////////////////////
std::vector<Field> Mtmp(nrhs,grid);
std::vector<Field> tmp(nrhs,grid);
std::vector<Field> Z(nrhs,grid); // Rename Z to R
std::vector<Field> MZ(nrhs,grid); // Rename MZ to Z
std::vector<Field> Q(nrhs,grid); //
std::vector<Field> MQ(nrhs,grid); // Rename to P
std::vector<Field> D(nrhs,grid);
std::vector<Field> AD(nrhs,grid);
/************************************************************************
* Preconditioned Block conjugate gradient rQ
* Generalise Sebastien Birk Thesis, after Dubrulle 2001.
* Introduce preconditioning following Saad Ch9
************************************************************************
* Dimensions:
*
* X,B etc... ==(Nferm x nrhs)
* Matrix A==(Nferm x Nferm)
*
* Nferm = Nspin x Ncolour x Ncomplex x Nlattice_site
* QC => Thin QR factorisation (google it)
*
* R = B-AX
* Z = Mi R
* QC = Z
* D = Q
* for k:
* R = AD
* Z = Mi R
* M = [D^dag R]^{-1}
* X = X + D M C
* QS = Q - Z.M
* D = Q + D S^dag
* C = S C
*/
Eigen::MatrixXcd m_DZ = Eigen::MatrixXcd::Identity(nrhs,nrhs);
Eigen::MatrixXcd m_M = Eigen::MatrixXcd::Identity(nrhs,nrhs);
Eigen::MatrixXcd m_zz = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_rr = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_C = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_Cinv = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_S = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_Sinv = Eigen::MatrixXcd::Zero(nrhs,nrhs);
Eigen::MatrixXcd m_tmp = Eigen::MatrixXcd::Identity(nrhs,nrhs);
Eigen::MatrixXcd m_tmp1 = Eigen::MatrixXcd::Identity(nrhs,nrhs);
GridStopWatch HDCGTimer;
//////////////////////////
// x0 = Vstart -- possibly modify guess
//////////////////////////
_Precon.Vstart(X,src);
//////////////////////////
// R = B-AX
//////////////////////////
for(int rhs=0;rhs<nrhs;rhs++){
// r0 = b -A x0
_FineLinop.HermOp(X[rhs],tmp[rhs]);
axpy (Z[rhs], -1.0,tmp[rhs], src[rhs]); // Computes R=Z=src - A X0
}
//////////////////////////////////
// Compute MZ = M1 Z = M1 B - M1 A x0
//////////////////////////////////
_Precon(Z,MZ);
//////////////////////////////////
// QC = Z
//////////////////////////////////
ThinQRfact (m_zz, m_C, m_Cinv, Q, MQ, Z, MZ);
//////////////////////////////////
// D=MQ
//////////////////////////////////
for(int b=0;b<nrhs;b++) D[b]=MQ[b]; // LLT rotation of the MZ basis of search dirs
std::cout << GridLogMessage<<"PrecBlockCGrQ vec computed initial residual and QR fact " <<std::endl;
_Precon.ResetTimers();
GridStopWatch M1Timer;
GridStopWatch M2Timer;
GridStopWatch M3Timer;
GridStopWatch LinalgTimer;
GridStopWatch InnerProdTimer;
HDCGTimer.Start();
std::vector<RealD> rn(nrhs);
for (int k=0;k<=MaxIterations;k++){
////////////////////
// Z = AD
////////////////////
M3Timer.Start();
for(int b=0;b<nrhs;b++) _FineLinop.HermOp(D[b], Z[b]);
M3Timer.Stop();
////////////////////
// MZ = M1 Z <==== the Multigrid preconditioner
////////////////////
M1Timer.Start();
_Precon(Z,MZ);
M1Timer.Stop();
////////////////////
// M = [D^dag Z]^{-1} = (<Ddag MZ>_M)^{-1} inner prod, generalising Saad derivation of Precon CG
////////////////////
InnerProdTimer.Start();
_BlockCGLinalg.InnerProductMatrix(m_DZ,D,Z);
InnerProdTimer.Stop();
m_M = m_DZ.inverse();
///////////////////////////
// X = X + D MC
///////////////////////////
m_tmp = m_M * m_C;
LinalgTimer.Start();
_BlockCGLinalg.MaddMatrix(X,m_tmp, D,X); // D are the search directions and X takes the updates
LinalgTimer.Stop();
///////////////////////////
// QS = Q - M Z
// (MQ) S = MQ - M (M1Z)
///////////////////////////
LinalgTimer.Start();
_BlockCGLinalg.MaddMatrix(tmp ,m_M, Z, Q,-1.0);
_BlockCGLinalg.MaddMatrix(Mtmp,m_M,MZ,MQ,-1.0);
ThinQRfact (m_zz, m_S, m_Sinv, Q, MQ, tmp, Mtmp);
LinalgTimer.Stop();
////////////////////////////
// D = MQ + D S^dag
////////////////////////////
m_tmp = m_S.adjoint();
LinalgTimer.Start();
_BlockCGLinalg.MaddMatrix(D,m_tmp,D,MQ);
LinalgTimer.Stop();
////////////////////////////
// C = S C
////////////////////////////
m_C = m_S*m_C;
////////////////////////////
// convergence monitor
////////////////////////////
m_rr = m_C.adjoint() * m_C;
RealD max_resid=0;
RealD rrsum=0;
RealD sssum=0;
RealD rr;
for(int b=0;b<nrhs;b++) {
rrsum+=real(m_rr(b,b));
sssum+=ssq[b];
rr = real(m_rr(b,b))/ssq[b];
if ( rr > max_resid ) max_resid = rr;
}
std::cout << GridLogMessage <<
"\t Prec BlockCGrQ Iteration "<<k<<" ave resid "<< std::sqrt(rrsum/sssum) << " max "<< std::sqrt(max_resid) <<std::endl;
if ( max_resid < Tolerance*Tolerance ) {
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ converged in "<<k<<" iterations and "<<HDCGTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : Linalg "<<LinalgTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : fine H "<<M3Timer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs PrecBlockCGrQ : prec M1 "<<M1Timer.Elapsed()<<std::endl;;
_Precon.ReportTimers("HDCG: mrhs PrecBlockCGrQ : ");
for(int rhs=0;rhs<nrhs;rhs++){
_FineLinop.HermOp(X[rhs],tmp[rhs]);
Field mytmp(grid);
axpy(mytmp,-1.0,src[rhs],tmp[rhs]);
RealD xnorm = sqrt(norm2(X[rhs]));
RealD srcnorm = sqrt(norm2(src[rhs]));
RealD tmpnorm = sqrt(norm2(mytmp));
RealD true_residual = tmpnorm/srcnorm;
std::cout<<GridLogMessage
<<"HDCG: true residual ["<<rhs<<"] is "<<true_residual
<<" solution "<<xnorm
<<" source "<<srcnorm
<<std::endl;
}
return;
}
}
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: PrecBlockCGrQ not converged "<<HDCGTimer.Elapsed()<<std::endl;
GRID_ASSERT(0);
}
virtual void SolveSingleSystem (std::vector<Field> &src, std::vector<Field> &x)
{
std::cout << GridLogMessage<<"HDCG: mrhs fPcg starting"<<std::endl;
src[0].Grid()->Barrier();
int nrhs = src.size();
std::vector<RealD> f(nrhs);
std::vector<RealD> rtzp(nrhs);
std::vector<RealD> rtz(nrhs);
std::vector<RealD> a(nrhs);
std::vector<RealD> d(nrhs);
std::vector<RealD> b(nrhs);
std::vector<RealD> rptzp(nrhs);
/////////////////////////////
// Set up history vectors
/////////////////////////////
int mmax = 3;
std::vector<std::vector<Field> > p(nrhs); for(int r=0;r<nrhs;r++) p[r].resize(mmax,grid);
std::vector<std::vector<Field> > mmp(nrhs); for(int r=0;r<nrhs;r++) mmp[r].resize(mmax,grid);
std::vector<std::vector<RealD> > pAp(nrhs); for(int r=0;r<nrhs;r++) pAp[r].resize(mmax);
std::vector<Field> z(nrhs,grid);
std::vector<Field> mp (nrhs,grid);
std::vector<Field> r (nrhs,grid);
std::vector<Field> mu (nrhs,grid);
//Initial residual computation & set up
std::vector<RealD> src_nrm(nrhs);
for(int rhs=0;rhs<nrhs;rhs++) {
src_nrm[rhs]=norm2(src[rhs]);
GRID_ASSERT(src_nrm[rhs]!=0.0);
}
std::vector<RealD> tn(nrhs);
GridStopWatch HDCGTimer;
//////////////////////////
// x0 = Vstart -- possibly modify guess
//////////////////////////
_Precon.Vstart(x,src);
for(int rhs=0;rhs<nrhs;rhs++){
// r0 = b -A x0
_FineLinop.HermOp(x[rhs],mmp[rhs][0]);
axpy (r[rhs], -1.0,mmp[rhs][0], src[rhs]); // Recomputes r=src-Ax0
}
//////////////////////////////////
// Compute z = M1 x
//////////////////////////////////
// This needs a multiRHS version for acceleration
_Precon(r,z);
std::vector<RealD> ssq(nrhs);
std::vector<RealD> rsq(nrhs);
std::vector<Field> pp(nrhs,grid);
for(int rhs=0;rhs<nrhs;rhs++){
rtzp[rhs] =real(innerProduct(r[rhs],z[rhs]));
p[rhs][0]=z[rhs];
ssq[rhs]=norm2(src[rhs]);
rsq[rhs]= ssq[rhs]*Tolerance*Tolerance;
// std::cout << GridLogMessage<<"mrhs HDCG: "<<rhs<<" k=0 residual "<<rtzp[rhs]<<" rsq "<<rsq[rhs]<<"\n";
}
_Precon.ResetTimers();
GridStopWatch M1Timer;
GridStopWatch M2Timer;
GridStopWatch M3Timer;
GridStopWatch LinalgTimer;
HDCGTimer.Start();
std::vector<RealD> rn(nrhs);
for (int k=0;k<=MaxIterations;k++){
int peri_k = k % mmax;
int peri_kp = (k+1) % mmax;
for(int rhs=0;rhs<nrhs;rhs++){
rtz[rhs]=rtzp[rhs];
M3Timer.Start();
d[rhs]= PcgM3(p[rhs][peri_k],mmp[rhs][peri_k]);
M3Timer.Stop();
a[rhs] = rtz[rhs]/d[rhs];
LinalgTimer.Start();
// Memorise this
pAp[rhs][peri_k] = d[rhs];
axpy(x[rhs],a[rhs],p[rhs][peri_k],x[rhs]);
rn[rhs] = axpy_norm(r[rhs],-a[rhs],mmp[rhs][peri_k],r[rhs]);
LinalgTimer.Stop();
}
// Compute z = M x (for *all* RHS)
M1Timer.Start();
_Precon(r,z);
M1Timer.Stop();
RealD max_rn=0.0;
LinalgTimer.Start();
for(int rhs=0;rhs<nrhs;rhs++){
rtzp[rhs] =real(innerProduct(r[rhs],z[rhs]));
// std::cout << GridLogMessage<<"HDCG::fPcg rhs"<<rhs<<" iteration "<<k<<" : inner rtzp "<<rtzp[rhs]<<"\n";
mu[rhs]=z[rhs];
p[rhs][peri_kp]=mu[rhs];
// Standard search direction p == z + b p
b[rhs] = (rtzp[rhs])/rtz[rhs];
int northog = (k>mmax-1)?(mmax-1):k; // This is the fCG-Tr(mmax-1) algorithm
for(int back=0; back < northog; back++){
int peri_back = (k-back)%mmax;
RealD pbApk= real(innerProduct(mmp[rhs][peri_back],p[rhs][peri_kp]));
RealD beta = -pbApk/pAp[rhs][peri_back];
axpy(p[rhs][peri_kp],beta,p[rhs][peri_back],p[rhs][peri_kp]);
}
RealD rrn=sqrt(rn[rhs]/ssq[rhs]);
RealD rtn=sqrt(rtz[rhs]/ssq[rhs]);
RealD rtnp=sqrt(rtzp[rhs]/ssq[rhs]);
std::cout<<GridLogMessage<<"HDCG:fPcg rhs "<<rhs<<" k= "<<k<<" residual = "<<rrn<<"\n";
if ( rrn > max_rn ) max_rn = rrn;
}
LinalgTimer.Stop();
// Stopping condition based on worst case
if ( max_rn <= Tolerance ) {
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg converged in "<<k<<" iterations and "<<HDCGTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : Linalg "<<LinalgTimer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : fine M3 "<<M3Timer.Elapsed()<<std::endl;;
std::cout<<GridLogMessage<<"HDCG: mrhs fPcg : prec M1 "<<M1Timer.Elapsed()<<std::endl;;
_Precon.ReportTimers("HDCG: mrhs fPcg : ");
for(int rhs=0;rhs<nrhs;rhs++){
_FineLinop.HermOp(x[rhs],mmp[rhs][0]);
Field tmp(grid);
axpy(tmp,-1.0,src[rhs],mmp[rhs][0]);
RealD mmpnorm = sqrt(norm2(mmp[rhs][0]));
RealD xnorm = sqrt(norm2(x[rhs]));
RealD srcnorm = sqrt(norm2(src[rhs]));
RealD tmpnorm = sqrt(norm2(tmp));
RealD true_residual = tmpnorm/srcnorm;
std::cout<<GridLogMessage
<<"HDCG: true residual ["<<rhs<<"] is "<<true_residual
<<" solution "<<xnorm
<<" source "<<srcnorm
<<" mmp "<<mmpnorm
<<std::endl;
}
return;
}
}
HDCGTimer.Stop();
std::cout<<GridLogMessage<<"HDCG: not converged "<<HDCGTimer.Elapsed()<<std::endl;
for(int rhs=0;rhs<nrhs;rhs++){
RealD xnorm = sqrt(norm2(x[rhs]));
RealD srcnorm = sqrt(norm2(src[rhs]));
std::cout<<GridLogMessage<<"HDCG: non-converged solution "<<xnorm<<" source "<<srcnorm<<std::endl;
}
}
RealD PcgM3(const Field & p, Field & mmp){
RealD dd;
_FineLinop.HermOp(p,mmp);
ComplexD dot = innerProduct(p,mmp);
dd=real(dot);
return dd;
}
};
//////////////////////////////////////////////////////////////////////
// ADEF-2 as an mrhs preconditioner object (Tang, Nabben, Vuik, Erlangga):
// M1 = [1 - Q A] M + Q with Q = P A_c^{-1} P^dag (deflated coarse solve)
// Vstart = Q b the coarse-corrected start (precise coarse solve)
// The coarse space is the D+1 multiRHS field throughout: the projector's
// mixed overloads take the vector of fine fields straight to it, and the
// deflator and coarse solver act on it. No per-rhs slices anywhere.
// The D+1 grid follows the solver's Nrhs through SetCoarseGridMrhs.
//////////////////////////////////////////////////////////////////////
// Projector_t defaults to a transfer operator whose STORE matches Field.
template<class Field, class CoarseField, class Projector_t = MultiRHSBlockProject<Field> >
class MrhsADEF2Preconditioner : public MrhsPreconditioner<Field>
{
public:
GridBase *grid; // fine
GridBase *coarsegridmrhs; // D+1, rhs innermost
LinearOperatorBase<Field> &_FineLinop;
LinearFunction<Field> &_Smoother;
LinearFunction<CoarseField> &_CoarseSolver; // in M1
LinearFunction<CoarseField> &_CoarseSolverPrecise; // in Vstart
Projector_t &_Projector; // store precision need not match Field
MultiRHSDeflation<CoarseField> &_Deflator; // nev==0: no deflation, zero coarse guess
MrhsADEF2Preconditioner(LinearOperatorBase<Field> &FineLinop,
LinearFunction<Field> &Smoother,
LinearFunction<CoarseField> &CoarseSolver,
LinearFunction<CoarseField> &CoarseSolverPrecise,
Projector_t &Projector,
MultiRHSDeflation<CoarseField> &Deflator,
GridBase *CoarseGridMrhs,
GridBase *FineGrid) :
_FineLinop(FineLinop), _Smoother(Smoother),
_CoarseSolver(CoarseSolver), _CoarseSolverPrecise(CoarseSolverPrecise),
_Projector(Projector), _Deflator(Deflator)
{
// The fine grid is given, NOT taken from the projector: the projector's
// grid carries its STORE's layout, which need not be this Field's (an
// fp32 preconditioner may project through an fp64 store, or the reverse).
grid = FineGrid;
coarsegridmrhs = CoarseGridMrhs;
};
// Store matches Field: the projector's grid IS this Field's grid.
MrhsADEF2Preconditioner(LinearOperatorBase<Field> &FineLinop,
LinearFunction<Field> &Smoother,
LinearFunction<CoarseField> &CoarseSolver,
LinearFunction<CoarseField> &CoarseSolverPrecise,
Projector_t &Projector,
MultiRHSDeflation<CoarseField> &Deflator,
GridBase *CoarseGridMrhs) :
MrhsADEF2Preconditioner(FineLinop,Smoother,CoarseSolver,CoarseSolverPrecise,
Projector,Deflator,CoarseGridMrhs,Projector.fine_grid) {};
void SetCoarseGridMrhs(GridBase *CoarseGridMrhs) { coarsegridmrhs = CoarseGridMrhs; }
// The coarse solver's starting guess: deflated, or zero
void CoarseGuess(CoarseField &src,CoarseField &guess)
{
this->DeflateTimer.Start();
if ( _Deflator.nev > 0 ) _Deflator.DeflateSources(src,guess);
else guess = Zero();
this->DeflateTimer.Stop();
}
// x_0 = Q b
virtual void Vstart(std::vector<Field> &x,std::vector<Field> &src)
{
CoarseField Csrc(coarsegridmrhs), Csol(coarsegridmrhs);
this->ProjectTimer.Start(); _Projector.blockProject(src,Csrc); this->ProjectTimer.Stop();
CoarseGuess(Csrc,Csol);
this->CoarseTimer.Start(); _CoarseSolverPrecise(Csrc,Csol); this->CoarseTimer.Stop();
this->PromoteTimer.Start(); _Projector.blockPromote(x,Csol); this->PromoteTimer.Stop();
}
// [1 - Q A] M in + Q in = Min + Q [in - A Min]
virtual void operator()(std::vector<Field> &in,std::vector<Field> &out)
{
int nrhs=in.size();
std::vector<Field> tmp(nrhs,grid), Min(nrhs,grid);
CoarseField Csrc(coarsegridmrhs), Csol(coarsegridmrhs);
this->SmoothTimer.Start();
for(int r=0;r<nrhs;r++) _Smoother(in[r],Min[r]);
this->SmoothTimer.Stop();
this->FineTimer.Start();
for(int r=0;r<nrhs;r++){
_FineLinop.HermOp(Min[r],out[r]);
axpy(tmp[r],-1.0,out[r],in[r]); // in - A Min
}
this->FineTimer.Stop();
this->ProjectTimer.Start(); _Projector.blockProject(tmp,Csrc); this->ProjectTimer.Stop();
CoarseGuess(Csrc,Csol);
this->CoarseTimer.Start(); _CoarseSolver(Csrc,Csol); this->CoarseTimer.Stop();
this->PromoteTimer.Start(); _Projector.blockPromote(tmp,Csol); this->PromoteTimer.Stop();
this->FineTimer.Start();
for(int r=0;r<nrhs;r++) axpy(out[r],1.0,Min[r],tmp[r]); // Min + Q[in - A Min]
this->FineTimer.Stop();
}
};
NAMESPACE_END(Grid);
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